The integration of Airborne Laser Scanning (ALS) survey into archaeological research and cultural heritage management has substantially added to our knowledge of archaeological remains in forested areas, and is changing our understanding of how these landscapes functioned in the past. Further, the results of ALS-based surveys of woodlands can now potentially be incorporated into micro-regional and landscape scale studies which rely on survey data, making an important contribution to our understanding of settlement patterns and land use - but doing so requires us to recognize and manage a host of biases inherent in ALS-based survey data. While many types of archaeological remains manifest as micro-topography, several important classes of features commonly appear as standing remains. The identification of these remains is important for archaeological prospection surveys based on ALS data. Standing structures in mixed scenes with vegetation are not well addressed by standard classification approaches. In this paper we propose an approach to the identification of these structures in the point cloud based on multi-scale measures of roughness, and measures of local density and normal orientation. We demonstrate this approach using discrete-return ALS data collected in the Franche-Comté region of France.
Point Clouds Segmentation of Mixed Scenes with Archeological Standing Remains: A Multi-Criteria and Multi-Scale Iterative Approach
Résumé
en
The integration of Airborne Laser Scanning (ALS) survey into archaeological research and cultural heritage management has substantially added to our knowledge of archaeological remains in forested areas, and is changing our understanding of how these landscapes functioned in the past. Further, the results of ALS-based surveys of woodlands can now potentially be incorporated into micro-regional and landscape scale studies which rely on survey data, making an important contribution to our understanding of settlement patterns and land use - but doing so requires us to recognize and manage a host of biases inherent in ALS-based survey data. While many types of archaeological remains manifest as micro-topography, several important classes of features commonly appear as standing remains. The identification of these remains is important for archaeological prospection surveys based on ALS data. Standing structures in mixed scenes with vegetation are not well addressed by standard classification approaches. In this paper we propose an approach to the identification of these structures in the point cloud based on multi-scale measures of roughness, and measures of local density and normal orientation. We demonstrate this approach using discrete-return ALS data collected in the Franche-Comté region of France.
Auteur(s)
Rachel Opitz1, 2
, Laure Nuninger3, 4, 2
1
University of Arkansas [Fayetteville]
( 310427 )
- 1 University of Arkansas, Fayetteville, AR 72701
- États-Unis
2
LEA ModelTER -
Laboratoire européen de modélisation des paysages et des territoires dans la longue durée
( 166496 )
- Besançon
- France
ZRC SAZU ( 307830 )
;
Centre National de la Recherche Scientifique ( 441569 )
;
3
MSHE -
Maison des Sciences de l'Homme et de l'Environnement Claude Nicolas Ledoux (UAR 3124)
( 2228 )
- 32-36, rue Mégevand 25030 BESANCON CEDEX
- France
Centre National de la Recherche Scientifique UAR3124 / USR3124 ( 441569 )
;
Paternité - Pas d'utilisation commerciale - Pas de modification
Nom de la revue
International Journal of Heritage in the Digital Era
(ISSN : 2047-4970, ISSN électronique : 2047-4989)
Publié par SAGE Journals
Revue non référencée dans Sherpa-Romeo
Date de publication
2014-07-01
Volume
3
Numéro
2
Domaine(s)
Sciences de l'Homme et Société/Archéologie et Préhistoire
Collaboration/Projet
LIEPPEC (LIdar pour l'Etude des Paysages Passés Et Contemporains)
LEA franco-slovène ModeLTER
Projet(s) Européen(s)
FEDER-ODIT
- Observatoire des Dynamiques Industrielles et Territoriales
Financement
Région Franche-Comté, UE-Feder
Mots-clés
en
Airborne Laser Scanning, archaeology, forest, standing structure, multi-scale, roughness, local density, normal orientation
Rachel Opitz, Laure Nuninger. Point Clouds Segmentation of Mixed Scenes with Archeological Standing Remains: A Multi-Criteria and Multi-Scale Iterative Approach. International Journal of Heritage in the Digital Era, 2014, 3 (2), pp.287-304. ⟨10.1260/2047-4970.3.2.287⟩. ⟨halshs-01099810⟩